Fast Implementation of Insect Multi-Target Detection Based on Multimodal Optimization
Entomological radars are important for scientific research of insect migration and early warning of migratory pests. However, insects are hard to detect because of their tiny size and highly maneuvering trajectory. Generalized Radon–Fourier transform (GRFT) has been proposed for effective weak maneu...
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doaj-608ddfe465324035a4baf86389dd56d02021-02-08T00:04:01ZengMDPI AGRemote Sensing2072-42922021-02-011359459410.3390/rs13040594Fast Implementation of Insect Multi-Target Detection Based on Multimodal OptimizationRui Wang0Yiming Zhang1Weiming Tian2Jiong Cai3Cheng Hu4Tianran Zhang5Radar Research Lab, School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, ChinaRadar Research Lab, School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, ChinaRadar Research Lab, School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, ChinaRadar Research Lab, School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, ChinaRadar Research Lab, School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, ChinaRadar Research Lab, School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, ChinaEntomological radars are important for scientific research of insect migration and early warning of migratory pests. However, insects are hard to detect because of their tiny size and highly maneuvering trajectory. Generalized Radon–Fourier transform (GRFT) has been proposed for effective weak maneuvering target detection by long-time coherent detection via jointly motion parameter search, but the heavy computational burden makes it impractical in real signal processing. Particle swarm optimization (PSO) has been used to achieve GRFT detection by fast heuristic parameter search, but it suffers from obvious detection probability loss and is only suitable for single target detection. In this paper, we convert the realization of GRFT into a multimodal optimization problem for insect multi-target detection. A novel niching method without radius parameter is proposed to detect unevenly distributed insect targets. Species reset and boundary constraint strategy are used to improve the detection performance. Simulation analyses of detection performance and computational cost are given to prove the effectiveness of the proposed method. Furthermore, real observation data acquired from a Ku-band entomological radar is used to test this method. The results show that it has better performance on detected target amount and track continuity in insect multi-target detection.https://www.mdpi.com/2072-4292/13/4/594generalized Radon–Fourier transformparticle swarm optimizationmultimodal optimization |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Rui Wang Yiming Zhang Weiming Tian Jiong Cai Cheng Hu Tianran Zhang |
spellingShingle |
Rui Wang Yiming Zhang Weiming Tian Jiong Cai Cheng Hu Tianran Zhang Fast Implementation of Insect Multi-Target Detection Based on Multimodal Optimization Remote Sensing generalized Radon–Fourier transform particle swarm optimization multimodal optimization |
author_facet |
Rui Wang Yiming Zhang Weiming Tian Jiong Cai Cheng Hu Tianran Zhang |
author_sort |
Rui Wang |
title |
Fast Implementation of Insect Multi-Target Detection Based on Multimodal Optimization |
title_short |
Fast Implementation of Insect Multi-Target Detection Based on Multimodal Optimization |
title_full |
Fast Implementation of Insect Multi-Target Detection Based on Multimodal Optimization |
title_fullStr |
Fast Implementation of Insect Multi-Target Detection Based on Multimodal Optimization |
title_full_unstemmed |
Fast Implementation of Insect Multi-Target Detection Based on Multimodal Optimization |
title_sort |
fast implementation of insect multi-target detection based on multimodal optimization |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2021-02-01 |
description |
Entomological radars are important for scientific research of insect migration and early warning of migratory pests. However, insects are hard to detect because of their tiny size and highly maneuvering trajectory. Generalized Radon–Fourier transform (GRFT) has been proposed for effective weak maneuvering target detection by long-time coherent detection via jointly motion parameter search, but the heavy computational burden makes it impractical in real signal processing. Particle swarm optimization (PSO) has been used to achieve GRFT detection by fast heuristic parameter search, but it suffers from obvious detection probability loss and is only suitable for single target detection. In this paper, we convert the realization of GRFT into a multimodal optimization problem for insect multi-target detection. A novel niching method without radius parameter is proposed to detect unevenly distributed insect targets. Species reset and boundary constraint strategy are used to improve the detection performance. Simulation analyses of detection performance and computational cost are given to prove the effectiveness of the proposed method. Furthermore, real observation data acquired from a Ku-band entomological radar is used to test this method. The results show that it has better performance on detected target amount and track continuity in insect multi-target detection. |
topic |
generalized Radon–Fourier transform particle swarm optimization multimodal optimization |
url |
https://www.mdpi.com/2072-4292/13/4/594 |
work_keys_str_mv |
AT ruiwang fastimplementationofinsectmultitargetdetectionbasedonmultimodaloptimization AT yimingzhang fastimplementationofinsectmultitargetdetectionbasedonmultimodaloptimization AT weimingtian fastimplementationofinsectmultitargetdetectionbasedonmultimodaloptimization AT jiongcai fastimplementationofinsectmultitargetdetectionbasedonmultimodaloptimization AT chenghu fastimplementationofinsectmultitargetdetectionbasedonmultimodaloptimization AT tianranzhang fastimplementationofinsectmultitargetdetectionbasedonmultimodaloptimization |
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1724280400957669376 |